Function sample_random_batch

baselines/utils.py:295–311

* inputs: - dataset (torch.utils.data.Dataset, required) An instance of torch.utils.data.Dataset. - batch_size (int, optional) Batch size. * returns: A mini-batch randomly sampled from the input dataset.

(dataset, batch_size=32)

def sample_random_batch(dataset, batch_size=32):
    """
    * inputs:
        - dataset (torch.utils.data.Dataset, required)
                An instance of torch.utils.data.Dataset.
        - batch_size (int, optional)
                Batch size.
    * returns:
            A mini-batch randomly sampled from the input dataset.
    """
    num_samples = len(dataset)
    batch = []
    for _ in range(min(batch_size, num_samples)):
        index = random.choice(range(0, num_samples))
        x = torch.unsqueeze(dataset[index], dim=0)
        batch.append(x)
    return torch.cat(batch, dim=0)


def get_deprocessor():